AI/ML Data Solution Architecture – Ability to define data architecture strategy that align with business goals for AI use cases and ensures data availability & data accuracy. Ensuring data quality by implementing and enforcing data governance policies and best practices Technology evaluation & selection – Execute Proof of concept and Proof of value for various technology solutions and frameworks Continuous Learning - Staying up to date with emerging technologies and trends in Data Engineering, AI / ML, and GenAI, and making recommendations for their adoption wherever appropriate Team Management – Responsible for leading a team of data architects and data engineers, as well as coordinating with vendors and technology partners Collaboration & communication – Collaborate and work closely with executives, stakeholder and business teams to effectively communicate architecture strategy & clearly articulate the business value.

Suitable candidate be able to demonstrate strong experience in the following areas

- Data Engineering – • Hands-on experience with data engineering tools such as Talend (or Informatica or AbInitio), Databricks (or Spark), and HVR (or Attunity or Golden Gate or Equalum). • Working knowledge of data build tools, Azure Data Factory, continuous integration and continuous delivery (CI/CD), automated testing, data lakes, data warehouses, big data, Collibra, and Unity Catalog • Basic knowledge of building analytics applications using Azure Purview, Power BI, Spotfire, and Azure Machine Learning.

AI & ML -

• Conceptualize & design end-to-end solution view of sourcing data, pre-processing data, feature stores, model development, evaluation, deployment & governance

• Define model development best practices, create POVs on emerging AI trends, drive the proposal responses, help solving complex analytics problems and strategize the end-toend implementation frameworks & methodologies

• Thorough understanding of database, streaming & analytics services offered by popular cloud platforms (Azure, AWS, GCP) and hands-on implementation of building machine learning pipeline with at least one of the popular cloud platforms

• Expertise on Large Language Model preferred with exposure to implementing generative AI using ChatGPT / Open AI and other models. Harvesting Models from open source will be an added advantage

• Good understanding of statistical analysis, data analysis and knowledge of data management & visualization techniques

• Exposure to other AI Platforms & products (Kore.ai, expert.ai, Dataiku etc.) desired • Hands-on development experience in Python/R is a must and additional hands-on experience on few other procedural/object-oriented programming languages (Java, C#, C++) is desirable.

• Leadership skills to drive the AI/ML related conversation amidst CXO, Senior Leadership and making impactful presentations to customer organizations

Stakeholder Management & Communication Skills

• Excellent communication, negotiation, influencing and stakeholder management skills

• Preferred to have experience in project management, particularly in executing projects using Agile delivery frameworks • Customer focus and excellent problem-solving skills

Qualification

BE or MTech (BSc or MSc) in engineering, sciences, or equivalent relevant experience required.

• Total 15+ years of experience and 10+ years of experience in building/managing/administrating data and analytics applications is required

• Designing solution architecture and present the architecture in architecture review forums

Additional Qualifications

• Ability to define best practices for data governance, data quality, and data lineage, and to operationalize those practices.

• Proven track record of designing and delivering solutions that comply with industry regulations and legislation such as GxP, SoX, HIPAA, and GDPR